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In this work the design and control of a reactive distillation column, described by a rigorous dynamic model, is tackled via two different optimization approaches.
The design of a state observer for the model is tackled.
Afterwards, the design of a state observer for this discrete-time SEIR epidemic model is tackled.
Likewise, the optimal recovery of time-varying parameters in a return-spread model is tackled.
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Natural identifiability problems with the new model are tackled properly in this case, by considering complete parameter posteriors instead of only the maximum likelihood estimate of model parameters.
Then the challenging topic of combining high-throughput docking techniques with receptor models is tackled.
Using as a basis known contrast agent pharmacokinetics and results of modelling techniques, the matter is tackled in this paper.
In this paper the problem is tackled by modelling the most influential but uncertain parameters as stochastic variables.
A character modeled after Sean Connery's Bond is tackled by Homer and killed after a parody of the laser scene from Goldfinger.
The problem is tackled by a model-based approach.
In this paper, parameter estimation for an epidemic model has been tackled in the framework of control theory.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com